badly written code may be slow (was hard to believe speed difference)

First, I love R and am grateful to be using this free and extremely
high quality software.

Recently I have been comparing two algorithms and naturally I
programmed in R first. It is so slow that I can almost feel its pain.
So I decided to do a comparison with Java. To draw 500,0000 truncated
normal, Java program takes 2 second and R takes 72 seconds. Not a
computer science major, I find it hard to understand how R can be so
slow.

R code:

normal.truncated <- function(mean, sd, lower, upper)
	 {
	    repeat
            {
		deviate = round( rnorm(1, mean, sd) );
                if(deviate<=upper && deviate>=lower) break;
            }
	    temp <- c(deviate+.5, deviate-.5, upper+.5, lower-.5);
	    result <- pnorm(temp, mean, sd);
	    prob <- (result[1] - result[2])/(result[3] - result[4]);

            return(c(deviate, prob));
     }

     print(date());

     n = 500000;
     result = numeric(n);

     for(i in 1:n) result[i] = normal.truncated(0,1, -10, 10)[1]
     print(date());

Java Code:

    package Mcdonald;
    import VisualNumerics.math.*;
    import java.util.*;

    public final class normal_univariate_truncated
    {
       public double harvest, prob;
       static Random ran_obj = new Random();

       public normal_univariate_truncated(double mean, double var,
double lower, double upper)
       {
          double sd = Math.sqrt(var);

          lower -= .5;
          upper += .5;
          double left = (lower - mean)/sd;
          double right = (upper - mean)/sd;
          double prob2 = Statistics.normalCdf(right) -
Statistics.normalCdf(left);

          while(true)
          {
              harvest = mean + ran_obj.nextGaussian()*sd;
              if(harvest>lower && harvest<upper) break;
          }

          harvest = Sfun.nearestInteger(harvest);
          left = (harvest - .5 - mean)/sd;
          right = (harvest + .5 - mean)/sd;
          double prob1 = Statistics.normalCdf(right) -
Statistics.normalCdf(left);

          prob = prob1/prob2;
       }


       public static void main(String[] useless)
       {
           System.out.println(new Date());
           int n = 500000;
           double[] result = new double[n];
           for(int i=0; i<n; i++)
           {
               normal_univariate_truncated obj = new
normal_univariate_truncated(0, 1, -10, 10);
               result[i] = obj.harvest;
           }
           System.out.println(new Date());
       }

    }


=====
Jason G. Liao, Ph.D.
Division of Biometrics
University of Medicine and Dentistry of New Jersey
335 George Street, Suite 2200
New Brunswick, NJ 08903-2688
phone (732) 235-8611, fax (732) 235-9777
http://www.geocities.com/jg_liao